Triple
T30568410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sillein |
E778052
|
entity |
| Predicate | countryDuringMostCommonUse |
P135380
|
FINISHED |
| Object | Austria-Hungary |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Austria-Hungary | Statement: [Sillein, countryDuringMostCommonUse, Austria-Hungary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryDuringMostCommonUse Context triple: [Sillein, countryDuringMostCommonUse, Austria-Hungary]
-
A.
countryNameUsage
Indicates how a country’s name is used or applied in a particular context or representation.
-
B.
primaryUseCountry
chosen
Indicates the country in which something is primarily used or most commonly utilized.
-
C.
countryOrRegionOfPrevalence
Indicates the country or geographic region where something (such as a condition, practice, or phenomenon) is most commonly found or occurs most frequently.
-
D.
countryOfSymbolicUse
Indicates the country in which something (such as a symbol, object, or element) is used in a symbolic or representative way.
-
E.
countryOrRegionUsed
Indicates that something is used within, or applies to, a specific country or geographic region.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f2249f8c148190ae7eb3912cde112a |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69ff878f41888190bcb3bc41ad26081a |
completed | May 9, 2026, 7:14 p.m. |
| PD | Predicate disambiguation | batch_69ff854082d88190aad3bfedf05e849f |
completed | May 9, 2026, 7:04 p.m. |
Created at: April 29, 2026, 8:21 p.m.